Facial Action Unit Detection via Adaptive Attention and Rela…
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Refs2023
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- DOI 10.1109/tip.2023.3277794
- PMID https://pubmed.ncbi.nlm.nih.gov/37310816
- OpenAlex ID W4377098248
- Type Article
- Language EN
- Published 01 Jan 2023
- Volume 32
- Pages 3354–3366
- Source IEEE Transactions on Image Processing
- Publisher Institute of Electrical and Electro…
- FWCI 3.18
- Countries 2
- Institutions 4
- Added 20 May 2023
- Updated 16 Oct 2026
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Facial Action Unit Detection via Adaptive Attention and Relation
Article 2023 EN Green
Facial action unit (AU) detection is challenging due to the difficulty in capturing correlated information from subtle and dynamic AUs. Existing methods often resort to the localization of correlated regions of AUs, in which predefining local AU attentions by correlated facial landmarks often discards essential parts, or learning global attention maps often contains irrelevant areas. Furthermore,…
40
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3.18
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5 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Zhiwen Shao | Ministry of Education of the P… (CN) Shanghai Jiao Tong University (CN) +1 | |
| 2 | Yong Zheng Zhou | Ministry of Education of the P… (CN) China University of Mining and… (CN) | |
| 3 | Jianfei Cai | Monash University (AU) | |
| 4 | Hancheng Zhu | Ministry of Education of the P… (CN) China University of Mining and… (CN) | |
| 5 | Rui Yao | Ministry of Education of the P… (CN) China University of Mining and… (CN) |
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